Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine
BackgroundStomach adenocarcinoma (STAD) is one of the primary contributors to deaths that are due to cancer globally. At the moment, STAD does not have any universally acknowledged biological markers, and its predictive, preventive, and personalized medicine (PPPM) remains sufficient. Oxidative stre...
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2023.1090906/full |
| _version_ | 1811165405430939648 |
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| author | Ying Dong Ying Dong Ying Dong Qihang Yuan Jie Ren Hanshuo Li Hui Guo Hewen Guan Xueyan Jiang Bing Qi Rongkuan Li |
| author_facet | Ying Dong Ying Dong Ying Dong Qihang Yuan Jie Ren Hanshuo Li Hui Guo Hewen Guan Xueyan Jiang Bing Qi Rongkuan Li |
| author_sort | Ying Dong |
| collection | DOAJ |
| description | BackgroundStomach adenocarcinoma (STAD) is one of the primary contributors to deaths that are due to cancer globally. At the moment, STAD does not have any universally acknowledged biological markers, and its predictive, preventive, and personalized medicine (PPPM) remains sufficient. Oxidative stress can promote cancer by increasing mutagenicity, genomic instability, cell survival, proliferation, and stress resistance pathways. As a direct and indirect result of oncogenic mutations, cancer depends on cellular metabolic reprogramming. However, their roles in STAD remain unclear.Method743 STAD samples from GEO and TCGA platforms were selected. Oxidative stress and metabolism-related genes (OMRGs) were acquired from the GeneCard Database. A pan-cancer analysis of 22 OMRGs was first performed. We categorized STAD samples by OMRG mRNA levels. Additionally, we explored the link between oxidative metabolism scores and prognosis, immune checkpoints, immune cell infiltration, and sensitivity to targeted drugs. A series of bioinformatics technologies were employed to further construct the OMRG-based prognostic model and clinical-associated nomogram.ResultsWe identified 22 OMRGs that could evaluate the prognoses of patients with STAD. Pan-cancer analysis concluded and highlighted the crucial part of OMRGs in the appearance and development of STAD. Subsequently, 743 STAD samples were categorized into three clusters with the enrichment scores being C2 (upregulated) > C3 (normal) > C1 (downregulated). Patients in C2 had the lowest OS rate, while C1 had the opposite. Oxidative metabolic score significantly correlates with immune cells and immune checkpoints. Drug sensitivity results reveal that a more tailored treatment can be designed based on OMRG. The OMRG-based molecular signature and clinical nomogram have good accuracy for predicting the adverse events of patients with STAD. Both transcriptional and translational levels of ANXA5, APOD, and SLC25A15 exhibited significantly higher in STAD samples.ConclusionThe OMRG clusters and risk model accurately predicted prognosis and personalized medicine. Based on this model, high-risk patients might be identified in the early stage so that they can receive specialized care and preventative measures, and choose targeted drug beneficiaries to deliver individualized medical services. Our results showed oxidative metabolism in STAD and led to a new route for improving PPPM for STAD. |
| first_indexed | 2024-04-10T15:36:41Z |
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| id | doaj.art-70a8a3bd1f8a4e8595eb130c84a1125d |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-04-10T15:36:41Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Endocrinology |
| spelling | doaj.art-70a8a3bd1f8a4e8595eb130c84a1125d2023-02-13T04:49:19ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922023-02-011410.3389/fendo.2023.10909061090906Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicineYing Dong0Ying Dong1Ying Dong2Qihang Yuan3Jie Ren4Hanshuo Li5Hui Guo6Hewen Guan7Xueyan Jiang8Bing Qi9Rongkuan Li10Gastroenterology and Hepatology Department, The Second Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of Infectious Diseases, The Second Affiliated Hospital of Dalian Medical University, Dalian, ChinaGraduate School of Dalian Medical University, Dalian Medical University, Dalian, ChinaDepartment of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of Oncology, The First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of Dermatology, The First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of Infectious Diseases, The Second Affiliated Hospital of Dalian Medical University, Dalian, ChinaBackgroundStomach adenocarcinoma (STAD) is one of the primary contributors to deaths that are due to cancer globally. At the moment, STAD does not have any universally acknowledged biological markers, and its predictive, preventive, and personalized medicine (PPPM) remains sufficient. Oxidative stress can promote cancer by increasing mutagenicity, genomic instability, cell survival, proliferation, and stress resistance pathways. As a direct and indirect result of oncogenic mutations, cancer depends on cellular metabolic reprogramming. However, their roles in STAD remain unclear.Method743 STAD samples from GEO and TCGA platforms were selected. Oxidative stress and metabolism-related genes (OMRGs) were acquired from the GeneCard Database. A pan-cancer analysis of 22 OMRGs was first performed. We categorized STAD samples by OMRG mRNA levels. Additionally, we explored the link between oxidative metabolism scores and prognosis, immune checkpoints, immune cell infiltration, and sensitivity to targeted drugs. A series of bioinformatics technologies were employed to further construct the OMRG-based prognostic model and clinical-associated nomogram.ResultsWe identified 22 OMRGs that could evaluate the prognoses of patients with STAD. Pan-cancer analysis concluded and highlighted the crucial part of OMRGs in the appearance and development of STAD. Subsequently, 743 STAD samples were categorized into three clusters with the enrichment scores being C2 (upregulated) > C3 (normal) > C1 (downregulated). Patients in C2 had the lowest OS rate, while C1 had the opposite. Oxidative metabolic score significantly correlates with immune cells and immune checkpoints. Drug sensitivity results reveal that a more tailored treatment can be designed based on OMRG. The OMRG-based molecular signature and clinical nomogram have good accuracy for predicting the adverse events of patients with STAD. Both transcriptional and translational levels of ANXA5, APOD, and SLC25A15 exhibited significantly higher in STAD samples.ConclusionThe OMRG clusters and risk model accurately predicted prognosis and personalized medicine. Based on this model, high-risk patients might be identified in the early stage so that they can receive specialized care and preventative measures, and choose targeted drug beneficiaries to deliver individualized medical services. Our results showed oxidative metabolism in STAD and led to a new route for improving PPPM for STAD.https://www.frontiersin.org/articles/10.3389/fendo.2023.1090906/fulloxidative stressmetabolismstomach adenocarcinomapredictive preventive personalized medicine (PPPM)molecular classification |
| spellingShingle | Ying Dong Ying Dong Ying Dong Qihang Yuan Jie Ren Hanshuo Li Hui Guo Hewen Guan Xueyan Jiang Bing Qi Rongkuan Li Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine Frontiers in Endocrinology oxidative stress metabolism stomach adenocarcinoma predictive preventive personalized medicine (PPPM) molecular classification |
| title | Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine |
| title_full | Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine |
| title_fullStr | Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine |
| title_full_unstemmed | Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine |
| title_short | Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine |
| title_sort | identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism related genes for stomach adenocarcinoma in the framework of predictive preventive and personalized medicine |
| topic | oxidative stress metabolism stomach adenocarcinoma predictive preventive personalized medicine (PPPM) molecular classification |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2023.1090906/full |
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